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AI Model Training Pipeline for Lab68Dev

Custom NLP model fine-tuned for task creation and tech support.

Quick Start

1. Setup Environment

# Create virtual environment
python -m venv venv

# Activate (Windows)
.\venv\Scripts\activate

# Activate (Linux/macOS)
source venv/bin/activate
# Install dependencies
pip install -r requirements.txt

2. Generate Training Data

python data/generate_dataset.py

3. Train Model

python train.py

4. Run Inference Server

# Set allowed CORS origins (optional, defaults to http://localhost:3000)
export ALLOWED_ORIGINS="http://localhost:3000,http://localhost:3001"

# Run the server
python inference/server.py

Environment Variables

  • ALLOWED_ORIGINS: Comma-separated list of allowed CORS origins (default: http://localhost:3000)
    • Example: http://localhost:3000,https://example.com
    • For production, set this to your specific domain(s) for security

Hardware Requirements

  • Minimum: RTX 4060 (8GB VRAM)
  • Recommended: RTX 4070+ (12GB+ VRAM)

Model Details

  • Base Model: TinyLlama-1.1B-Chat-v1.0
  • Fine-tuning: LoRA (rank 16)
  • Dataset: ~4000 synthetic examples (task creation + tech Q&A)